Systematic threat identification using the STRIDE methodology for security analysis and documentation.
Works with
Covers six threat categories (Spoofing, Tampering, Repudiation, Information Disclosure, Denial of Service, Elevation of Privilege) with specific questions and control families for each
Includes ready-to-use templates for threat model documents, data flow diagram analysis, and risk assessment matrices with prioritization
Provides Python utilities for automated threat enumeration, que
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionstride-analysis-patternsExecute the skills CLI command in your project's root directory to begin installation:
Fetches stride-analysis-patterns from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate stride-analysis-patterns. Access via /stride-analysis-patterns in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Systematic threat identification using the STRIDE methodology.
S - Spoofing → Authentication threats
T - Tampering → Integrity threats
R - Repudiation → Non-repudiation threats
I - Information → Confidentiality threats
Disclosure
D - Denial of → Availability threats
Service
E - Elevation of → Authorization threats
Privilege
| Category | Question | Control Family |
|---|---|---|
| Spoofing | Can attacker pretend to be someone else? | Authentication |
| Tampering | Can attacker modify data in transit/rest? | Integrity |
| Repudiation | Can attacker deny actions? | Logging/Audit |
| Info Disclosure | Can attacker access unauthorized data? | Encryption |
| DoS | Can attacker disrupt availability? | Rate limiting |
| Elevation | Can attacker gain higher privileges? | Authorization |
# Threat Model: [System Name]
## 1. System Overview
### 1.1 Description
[Brief description of the system and its purpose]
### 1.2 Data Flow Diagram
[User] --> [Web App] --> [API Gateway] --> [Backend Services] | v [Database]
### 1.3 Trust Boundaries
- **External Boundary**: Internet to DMZ
- **Internal Boundary**: DMZ to Internal Network
- **Data Boundary**: Application to Database
## 2. Assets
| Asset | Sensitivity | Description |
|-------|-------------|-------------|
| User Credentials | High | Authentication tokens, passwords |
| Personal Data | High | PII, financial information |
| Session Data | Medium | Active user sessions |
| Application Logs | Medium | System activity records |
| Configuration | High | System settings, secrets |
## 3. STRIDE Analysis
### 3.1 Spoofing Threats
| ID | Threat | Target | Impact | Likelihood |
|----|--------|--------|--------|------------|
| S1 | Session hijacking | User sessions | High | Medium |
| S2 | Token forgery | JWT tokens | High | Low |
| S3 | Credential stuffing | Login endpoint | High | High |
**Mitigations:**
- [ ] Implement MFA
- [ ] Use secure session management
- [ ] Implement account lockout policies
### 3.2 Tampering Threats
| ID | Threat | Target | Impact | Likelihood |
|----|--------|--------|--------|------------|
| T1 | SQL injection | Database queries | Critical | Medium |
| T2 | Parameter manipulation | API requests | High | High |
| T3 | File upload abuse | File storage | High | Medium |
**Mitigations:**
- [ ] Input validation on all endpoints
- [ ] Parameterized queries
- [ ] File type validation
### 3.3 Repudiation Threats
| ID | Threat | Target | Impact | Likelihood |
|----|--------|--------|--------|------------|
| R1 | Transaction denial | Financial ops | High | Medium |
| R2 | Access log tampering | Audit logs | Medium | Low |
| R3 | Action attribution | User actions | Medium | Medium |
**Mitigations:**
- [ ] Comprehensive audit logging
- [ ] Log integrity protection
- [ ] Digital signatures for critical actions
### 3.4 Information Disclosure Threats
| ID | Threat | Target | Impact | Likelihood |
|----|--------|--------|--------|------------|
| I1 | Data breach | User PII | Critical | Medium |
| I2 | Error message leakage | System info | Low | High |
| I3 | Insecure transmission | Network traffic | High | Medium |
**Mitigations:**
- [ ] Encryption at rest and in transit
- [ ] Sanitize error messages
- [ ] Implement TLS 1.3
### 3.5 Denial of Service Threats
| ID | Threat | Target | Impact | Likelihood |
|----|--------|--------|--------|------------|
| D1 | Resource exhaustion | API servers | High | High |
| D2 | Database overload | Database | Critical | Medium |
| D3 | Bandwidth saturation | Network | High | Medium |
**Mitigations:**
- [ ] Rate limiting
- [ ] Auto-scaling
- [ ] DDoS protection
### 3.6 Elevation of Privilege Threats
| ID | Threat | Target | Impact | Likelihood |
|----|--------|--------|--------|------------|
| E1 | IDOR vulnerabilities | User resources | High | High |
| E2 | Role manipulation | Admin access | Critical | Low |
| E3 | JWT claim tampering | Authorization | High | Medium |
**Mitigations:**
- [ ] Proper authorization checks
- [ ] Principle of least privilege
- [ ] Server-side role validation
## 4. Risk Assessment
### 4.1 Risk Matrix
IMPACT
Low Med High Crit
Low 1 2 3 4
L Med 2 4 6 8 I High 3 6 9 12 K Crit 4 8 12 16
### 4.2 Prioritized Risks
| Rank | Threat | Risk Score | Priority |
|------|--------|------------|----------|
| 1 | SQL Injection (T1) | 12 | Critical |
| 2 | IDOR (E1) | 9 | High |
| 3 | Credential Stuffing (S3) | 9 | High |
| 4 | Data Breach (I1) | 8 | High |
## 5. Recommendations
### Immediate Actions
1. Implement input validation framework
2. Add rate limiting to authentication endpoints
3. Enable comprehensive audit logging
### Short-term (30 days)
1. Deploy WAF with OWASP ruleset
2. Implement MFA for sensitive operations
3. Encrypt all PII at rest
### Long-term (90 days)
1. Security awareness training
2. Penetration testing
3. Bug bounty program
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Dict, Optional
import json
class StrideCategory(Enum):
SPOOFING = "S"
TAMPERING = "T"
REPUDIATION = "R"
INFORMATION_DISCLOSURE = "I"
DENIAL_OF_SERVICE = "D"
ELEVATION_OF_PRIVILEGE = "E"
class Impact(Enum):
LOW = 1
MEDIUM = 2
HIGH = 3
CRITICAL = 4
class Likelihood(Enum):
LOW = 1
MEDIUM = 2
HIGH = 3
CRITICAL = 4
@dataclass
class Threat:
id: str
category: StrideCategory
title: str
description: str
target: str
impact: Impact
likelihood: Likelihood
mitigations: List[str] = field(default_factory=list)
status: str = "open"
@property
def risk_score(self) -> int:
return self.impact.value * self.likelihood.value
@property
def risk_level(self) -> str:
score = self.risk_score
if score >= 12:
return "Critical"
elif score >= 6:
return "High"
elif score >= 3:
return "Medium"
return "Low"
@dataclass
class Asset:
name: str
sensitivity: str
description: str
data_classification: str
@dataclass
class TrustBoundary:
name: str
description: str
from_zone: str
to_zone: str
@dataclass
class ThreatModel:
name: str
version: str
description: str
assets: List[Asset] = field(default_factory=list)
boundaries: List[TrustBoundary] = field(default_factory=list)
threats: List[Threat] = field(default_factory=list)
def add_threat(self, threat: Threat) -> None:
self.threats.append(threat)
def get_threats_by_category(self, category: StrideCategory) -> List[Threat]:
return [t for t in self.threats if t.category == category]
✓Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
✓Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.5★★★★★31 reviews- LLi Sanchez★★★★★Dec 8, 2024
Useful defaults in stride-analysis-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- SSofia Park★★★★★Nov 27, 2024
stride-analysis-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- HHarper Reddy★★★★★Nov 11, 2024
stride-analysis-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
- CCarlos Sanchez★★★★★Oct 18, 2024
Keeps context tight: stride-analysis-patterns is the kind of skill you can hand to a new teammate without a long onboarding doc.
- NNoah Tandon★★★★★Oct 2, 2024
Registry listing for stride-analysis-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
- OOshnikdeep★★★★★Sep 13, 2024
I recommend stride-analysis-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- CChen Sharma★★★★★Sep 13, 2024
Solid pick for teams standardizing on skills: stride-analysis-patterns is focused, and the summary matches what you get after install.
- NNoah Sanchez★★★★★Sep 9, 2024
stride-analysis-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.
- SSofia Agarwal★★★★★Aug 28, 2024
Solid pick for teams standardizing on skills: stride-analysis-patterns is focused, and the summary matches what you get after install.
- GGanesh Mohane★★★★★Aug 4, 2024
Useful defaults in stride-analysis-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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